We consider the problem of downlink training and channel estimation in frequency division
duplex (FDD) massive MIMO systems, where the base station (BS) equipped with a large …

Massive multiple-input multiple-output is a promising physical layer technology for 5G
wireless communications due to its capability of high spectrum and energy efficiency, high …

This letter proposes a deep learning-based pilot design scheme to minimize the sum mean
square error (MSE) of channel estimation for multi-user distributed massive multiple-input …

Massive multiple-input multiple-output (MIMO) is one of the most promising techniques for
next generation wireless communications due to its superior capability to provide high …

The deep convolutional neural network (CNN) is exploited in this work to conduct the
challenging channel estimation for mmWave massive multiple input multiple output (MIMO) …

The combination of cell-free massive multiple-input multiple-output (MIMO) systems along
with millimeter-wave (mmWave) bands is indeed one of most promising technological …

Channel estimation is crucial for massive multiple-input multiple-output (MIMO) systems to
scale up multi-user MIMO, providing significant improvement in spectral and energy …

In this paper, we propose a data-driven deep learning (DL) approach to jointly design the
pilot signals and channel estimator for wideband massive multiple-input multiple-output …

Millimeter-wave massive multiple-input multiple-output (MIMO) can use a lens antenna array
to considerably reduce the number of radio frequency (RF) chains, but channel estimation is …

Motivated by recent developments in time-division duplex massive multiple-input multiple-
output (MIMO) systems, this paper investigates semi-blind channel estimation for multiuser …